Mitigating the Filter Bubble While Maintaining Relevance-Reference-Cited by-同舟云学术

Mitigating the Filter Bubble While Maintaining Relevance

Published:2022-07-06 Issue: Volume: Page:
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Container-title:Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval
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Author:

Gao Zhaolin¹,Shen Tianshu¹,Mai Zheda²,Bouadjenek Mohamed Reda³,Waller Isaac¹,Anderson Ashton¹,Bodkin Ron⁴,Sanner Scott¹

Affiliation:

1. University of Toronto, Toronto, ON, Canada

2. Optimy AI, Toronto, ON, Canada

3. Deakin University, Geelong, Australia

4. Vector Institute for Artificial Intelligence, Toronto, ON, Canada

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3477495.3531890

Reference20 articles.

1. Guy Aridor , Duarte Goncalves , and Shan Sikdar . 2020. Deconstructing the Filter Bubble: User Decision-Making And Recommender Systems . Association for Computing Machinery , New York, NY, USA , 82--91. Guy Aridor, Duarte Goncalves, and Shan Sikdar. 2020. Deconstructing the Filter Bubble: User Decision-Making And Recommender Systems .Association for Computing Machinery, New York, NY, USA, 82--91.

2. The use of MMR, diversity-based reranking for reordering documents and producing summaries

3. Allison J. B. Chaney , Brandon M. Stewart , and Barbara E. Engelhardt . 2018. How Algorithmic Confounding in Recommendation Systems Increases Homogeneity and Decreases Utility . In Proceedings of the 12th ACM Conference on Recommender Systems ( Vancouver, British Columbia, Canada) (RecSys '18). Association for Computing Machinery, New York, NY, USA, 224--232. Allison J. B. Chaney, Brandon M. Stewart, and Barbara E. Engelhardt. 2018. How Algorithmic Confounding in Recommendation Systems Increases Homogeneity and Decreases Utility. In Proceedings of the 12th ACM Conference on Recommender Systems (Vancouver, British Columbia, Canada) (RecSys '18). Association for Computing Machinery, New York, NY, USA, 224--232.

4. Filter Bubbles, Echo Chambers, and Online News Consumption

5. Understanding Echo Chambers in E-commerce Recommender Systems

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